What is the internal state of a Simple Neural Attentive Meta-Learner(SNAIL)?
Here's what I understand, welcome to point out any mistakes.

When starting a new episode(but still in the same task), SNAIL does not clear its batches. Instead, it makes decisions based on the current observation and observation-action pairs from the previous episode. In this way, it keeps knowledge of the previous episode whereby achieving few-shot learning in the test time.